Adaptive Channel-State-Information Feedback in Integrated Sensing and Communication Systems

Area of Science:

• Wireless communication
• Signal processing
• Sensing systems

Background:

• Integrated sensing and communication systems aim to minimize signaling overhead.
• Reducing feedback rate for channel state information (CSI) is crucial for efficient system design.
• Current methods face challenges in quantifying channel variation and determining optimal thresholds for reduced feedback.

Purpose of the Study:

• To propose a threshold-based procedure for reducing CSI feedback rate in integrated sensing and communication systems.
• To quantify channel variation using metrics like Euclidean distance, time-reversal, and frequency-reversal resonating strength.
• To develop adaptive thresholding and reconstruction schemes for accurate sensing with minimized feedback.

Main Methods:

• Quantified channel variation using Euclidean distance, time-reversal resonating strength, and frequency-reversal resonating strength.
• Designed an adaptive algorithm to select thresholds, minimizing feedback rate while ensuring sensing accuracy.
• Proposed two reconstruction schemes for improved accuracy with irregular channel measurements.
• Evaluated performance using real and synthetic channel measurements, considering estimation and synchronization errors.

Main Results:

• Achieved a 50% reduction in feedback amount while maintaining good sensing performance for range and velocity estimations.
• Demonstrated that the Euclidean distance metric effectively captures diverse human movements with high channel variation.
• Validated the proposed scheme's robustness against channel estimation and synchronization errors.

Conclusions:

• The proposed threshold-based CSI feedback reduction procedure is effective for integrated sensing and communication systems.
• Adaptive thresholding and reconstruction schemes enhance sensing accuracy and minimize feedback rates.
• Euclidean distance is a superior metric for capturing human movement signatures in high channel variation scenarios.